Local and regional authorities in the EU create the plans for water management to ensure that water resources are managed after sustainability, with a wide range of factors such as climate, landscape and human activities into account. These plans take into account the role of water -related ecosystem services – the functions carried out by natural areas that benefit people through modification of water quality, flow and availability. For example, forests and wetlands can reduce the outflow and improve the groundwater loading.
The water management plans usually take into account the different land uses in an area in their predictive model, but may not take into account the landscape configuration in order to obtain information about the size, shape and connectivity of the patches of a certain land use. However, studies have shown that the country usage configuration has a significant influence on water -related ecosystem services. In this study, researchers find that there were only limited guidelines on how these effects should influence management and guideline decisions. Therefore, they examined how configuration data can be used in modeling, which provides land management for water -related ecosystem services.
Concentration on an area of around 8,000 km2 In the Arno River basin in Tuscany, Italy, they used data models to evaluate the importance of landscape configuration factors for the provision of ecosystem services. They taken into account nine landscape configuration metrics related to the size, shape and distribution of land use spots and rated them against three indicators for the provision of water supply services for water -related ecosystems:
- Water yield – the available water supply;
- Drain water that runs over the floor (instead of soaking in it or running through watercourses);
- Groundwater charging – water that flows into the groundwater supply.
The researchers analyzed the variation in every indicator and evaluated the differences over time and between the places. They used data models in addition to historical data from 2000 to 2020 to evaluate the importance of the landscape configuration factors. They did this by once performing the models with the historical data and then again with replacement values for a factor that was created randomly. The difference in the accuracy of the prediction of the model in any case was how important this factor was.
The researchers used two models:
- The Bigbang model developed by the Italian Institute for Environmental Protection and Research to make predictions at national and regional level;
- The SWAT model (Soil and Water Assessment Tool), which was presented in the Journal Ecohydrology in 2023 and was developed for the high analysis of complex water catchment areas.
The results of both models showed that landscape configuration factors were associated with predictive accuracy. In the SWAT model, the significance of 43% was sufficient for the time deviation of the water yield and in the evaluation of the spatial variation of the groundwater charging. In the Bigbang model, it was 13% important for the spatial variation of the groundwater loading to 2% for temporal variations of the drain.
When modeling the drainage, the coniferous forest areas were particularly significant, with the number of patches corresponding to a decrease in variability. In the case of groundwater loads, the importance of the forests of broad forests was remarkable, which reduced the variability of this indicator. For the water yield, they emphasized that the forest areas reduced the variation less effectively if they were more fragmented over the landscape.
The researchers presented detailed illustrations on the importance of every specific metric in every scenario (ie every combination of indicator, model and temporal/spatial variation). They have highlighted the importance of certain metrics in certain scenarios. For example, they identified the core area index (the proportion of the total area, which is located in a patch and not on the edge) for broad leaf forests as a significant influence on the spatial and temporal deviation of the drain according to the SWAT model and on the spatial variation of the water yield according to Bigbang.
The study showed how the use of land use configuration metrics could influence the management decisions. This included:
- Prioritization of Avorstier activities that increase forest connectivity in order to stabilize the drainage and reduce soil erosion;
- Implementation of Agroforst in areas with complex forms of land use to improve groundwater loading and the reliability of the groundwater supply;
- Plan over the land use in a way that ensures a significant level of core area to improve water availability and yield of water.
According to the researchers, these results showed the potential value of the involvement of the configuration metrics of land use in the models of water -related ecosystem services that were used to inform the planning and political development of land use. They argued for the development of models that would include such metrics and their use in guidelines, planning and management.
Some study restrictions were found, including the spatial dissolution of the analysis. Further studies could take into account the development of optimal landscape metrics and examinations of the role of specific metrics when predicting the behavior of water -related ecosystem services.
Reference:
J. Jeitany, M. Nussbaum, T. Pacetti, B. Schröder, E. Caporali, E. (2024) Landscape metrics as predictors for water -related ecosystem services: insights from hydrological modeling and data -based approaches used on the Arno River Basin, Italy. Science of the total environment 954: 176567
https://doi.org/10.1016/J.Scitotenv.2024.176567
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“Science for environmental policy”: European Commission DG Environment News Alert Service, edited by SCU, the University of the West England, Bristol.
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The content and views contained in science for environmental policy are based on independent, peer -checked research and do not necessarily reflect the position of the European Commission. Please note that this article is a summary of just one study. Other studies can come to different conclusions.